‘Hard Fork’ Live, Part 3: Differing Visions of an A.I. Future
We’re back with our final installment from Hard Fork Live, recorded at the Yerba Buena Center for the Arts in San Francisco. In this episode, we’re joined by Sayash Kapoor and Daniel Kokotajlo to talk about their differing visions of A.I. transformation: why Sayash thinks A.I. will diffuse throughout society like a “normal” technology, and why Daniel thinks an unprecedented acceleration is just around the corner. Then we’re joined by George Ekas from Toborlife AI, along with his dancing robot Toby. Finally, the podcaster Dwarkesh Patel drops by, and we take a few questions from the live audience.
Guests:
Sayash Kapoor, an A.I. researcher at Princeton University and a co-author of the newsletter “AI as Normal Technology”
Daniel Kokotajlo, the executive director of the AI Futures Project and a co-author of “AI 2027”
George Ekas, the director of engineering at Toberlife AI
Dwarkesh Patel, a tech podcaster
Additional Reading:
This A.I. Forecast Predicts Storms Ahead
AI as Normal Technology
Common Ground Between AI 2027 & AI as Normal Technology
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How To AI: A Practical Business Q&A With Three Experts
As more companies push AI in their workplaces, the technology is rapidly reshaping the way many of us do our jobs. But a lot of people — from entry-level employees to the C-Suite — are still in the dark about the limits of AI, its best uses, and how to make it work for them.
We called in a panel of AI experts to answer some our listeners’ burning questions about how to use it at work: Sayash Kapoor, co-author of the book AI Snake Oil: What Artificial Can Do, What it Can’t, and How to Tell the Difference and the Substack AI as Normal Technology; Rajeev Kapur, CEO of 1105 Media and author of the book AI Made Simple: A Beginner's Guide to Generative Intelligence; and futurist and author Amy Webb, founder and CEO of the consulting firm Future Today Strategy Group.
Kara, Sayash, Rajeev and Amy break down everything from how vibe coding works to thornier questions around privacy and regulation. They talk about how young people can prepare themselves to enter the workforce, and how all of us can develop skills to stay relevant. And, of course, they weigh in on the question so many of us are asking right now: Is AI coming for my job?
Questions? Comments? Email us at on@voxmedia.com or find us on YouTube, Instagram, TikTok, and Bluesky @onwithkaraswisher.
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Sayash Kapoor - How seriously should we take AI X-risk? (ICML 1/13)
How seriously should governments take the threat of existential risk from AI, given the lack of consensus among researchers? On the one hand, existential risks (x-risks) are necessarily somewhat speculative: by the time there is concrete evidence, it may be too late. On the other hand, governments must prioritize — after all, they don’t worry too much about x-risk from alien invasions.
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Sayash Kapoor is a computer science Ph.D. candidate at Princeton University's Center for Information Technology Policy. His research focuses on the societal impact of AI. Kapoor has previously worked on AI in both industry and academia, with experience at Facebook, Columbia University, and EPFL Switzerland. He is a recipient of a best paper award at ACM FAccT and an impact recognition award at ACM CSCW. Notably, Kapoor was included in TIME's inaugural list of the 100 most influential people in AI.
Sayash Kapoor
https://x.com/sayashk
https://www.cs.princeton.edu/~sayashk/
Arvind Narayanan (other half of the AI Snake Oil duo)
https://x.com/random_walker
AI existential risk probabilities are too unreliable to inform policy
https://www.aisnakeoil.com/p/ai-existential-risk-probabilities
Pre-order AI Snake Oil Book
https://amzn.to/4fq2HGb
AI Snake Oil blog
https://www.aisnakeoil.com/
AI Agents That Matter
https://arxiv.org/abs/2407.01502
Shortcut learning in deep neural networks
https://www.semanticscholar.org/paper/Shortcut-learning-in-deep-neural-networks-Geirhos-Jacobsen/1b04936c2599e59b120f743fbb30df2eed3fd782
77% Of Employees Report AI Has Increased Workloads And Hampered Productivity, Study Finds
https://www.forbes.com/sites/bryanrobinson/2024/07/23/employees-report-ai-increased-workload/
TOC:
00:00:00 Intro
00:01:57 How seriously should we take Xrisk threat?
00:02:55 Risk too unrealiable to inform policy
00:10:20 Overinflated risks
00:12:05 Perils of utility maximisation
00:13:55 Scaling vs airplane speeds
00:17:31 Shift to smaller models?
00:19:08 Commercial LLM ecosystem
00:22:10 Synthetic data
00:24:09 Is AI complexifying our jobs?
00:25:50 Does ChatGPT make us dumber or smarter?
00:26:55 Are AI Agents overhyped?
00:28:12 Simple vs complex baselines
00:30:00 Cost tradeoff in agent design
00:32:30 Model eval vs downastream perf
00:36:49 Shortcuts in metrics
00:40:09 Standardisation of agent evals
00:41:21 Humans in the loop
00:43:54 Levels of agent generality
00:47:25 ARC challenge
Assessing the Risks of Open AI Models with Sayash Kapoor - #675
Today we’re joined by Sayash Kapoor, a Ph.D. student in the Department of Computer Science at Princeton University. Sayash walks us through his paper: "On the Societal Impact of Open Foundation Models.” We dig into the controversy around AI safety, the risks and benefits of releasing open model weights, and how we can establish common ground for assessing the threats posed by AI. We discuss the application of the framework presented in the paper to specific risks, such as the biosecurity risk of open LLMs, as well as the growing problem of "Non Consensual Intimate Imagery" using open diffusion models.
The complete show notes for this episode can be found at twimlai.com/go/675.
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